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Robust Online Scale Estimation in Time Series: A Regression-Free Approach
Author(s) -
Sarah Gelper,
Karen Schettlinger,
Christophe Croux,
Ursula Gather
Publication year - 2007
Publication title -
ssrn electronic journal
Language(s) - English
Resource type - Journals
ISSN - 1556-5068
DOI - 10.2139/ssrn.1089390
Subject(s) - series (stratigraphy) , scale (ratio) , computer science , regression , time series , statistics , econometrics , mathematics , geography , cartography , paleontology , biology
This paper presents variance extraction procedures for univariate time series. The volatility of a times series is monitored allowing for non-linearities, jumps and outliers in the level. The volatility is measured using the height of triangles formed by consecutive observations of the time series. This idea was proposed by Rousseeuw and Hubert (1996, Regression-free and robust estimation of scale for bivariate data, Computational Statistics and Data Analysis, 21, 67{85) in the bivariate setting. This paper extends their procedure to apply for online scale estimation in time series analysis. The statistical properties of the new methods are derived and nite sample properties are given. A nancial and a medical application illustrate the use of the procedures.

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